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US11197641B2 - Communication device, abnormality notification system, and abnormality notification method - Google Patents

Communication device, abnormality notification system, and abnormality notification method Download PDF

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Publication number
US11197641B2
US11197641B2 US16/532,713 US201916532713A US11197641B2 US 11197641 B2 US11197641 B2 US 11197641B2 US 201916532713 A US201916532713 A US 201916532713A US 11197641 B2 US11197641 B2 US 11197641B2
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target person
body temperature
sensor
abnormality
sensing target
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US20190357857A1 (en
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Toshiaki Tanaka
Masaru Yamaoka
Kenji Masuda
Kazuhiro Watanabe
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Panasonic Intellectual Property Management Co Ltd
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Panasonic Intellectual Property Management Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • A61B5/015—By temperature mapping of body part
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient; User input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0008—Temperature signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1115—Monitoring leaving of a patient support, e.g. a bed or a wheelchair
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1118—Determining activity level
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
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    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0075—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6889—Rooms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
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    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6892—Mats

Definitions

  • the present disclosure relates to a technique for abnormality notification to a sensing target person.
  • PTL 1 has an object of intuitively grasping a situation of a nursed person, and discloses storing a caricatured display image for each of a plurality of levels of vital data. There is then displayed a display image according to a level of the vital data on the nursed person acquired by a vital data acquisition unit.
  • PTL 2 discloses a technique of simultaneously detecting body temperature abnormality of a plurality of persons in accordance with a thermal image read by an infrared camera.
  • a person has body temperature rhythm of body temperature varying in one day.
  • the body temperature rhythm thus needs to be taken into consideration for accurate detection of body temperature abnormality.
  • PTL 1 and PTL 2 each fail to take the body temperature rhythm of the sensing target person into consideration for accurate detection of body temperature abnormality.
  • the present disclosure provides a technique of accurately detecting body temperature abnormality of a sensing target person.
  • a communication device configured to notify of abnormality of a sensing target person, and includes a first sensor configured to measure a state of the sensing target person to acquire first measurement data, a second sensor configured to measure a body temperature of the sensing target person to acquire second measurement data, and a memory unit configured to store a reference body temperature for a single or each of a plurality of predetermined states of the sensing target person.
  • the communication device further includes a state determiner configured to determine whether or not the sensing target person is in the single or any one of the plurality of predetermined states in accordance with the first measurement data acquired by the first sensor, and an abnormality determiner configured to compare the reference body temperature for the single or any one of the plurality of predetermined states with the body temperature of the sensing target person indicated by the second measurement data acquired by the second sensor, when the state determiner determines that the sensing target person is in the single or any one of the plurality of predetermined states.
  • the abnormality determiner determines whether or not the sensing target person has a body temperature abnormality.
  • the abnormality determiner generates alerting information for abnormality notification when determining that the sensing target person has body temperature abnormality.
  • the present disclosure further provides an abnormality notification system configured to notify of abnormality of a sensing target person and including the communication device described above and a terminal device connected to the communication device via a network.
  • the terminal device includes an output unit configured to output the alerting information generated by the abnormality determiner of the communication device.
  • the present disclosure provides an abnormality notification method with use of an abnormality notification system configured to notify of abnormality of a sensing target person.
  • the abnormality notification method includes (a) measuring a state of the sensing target person with use of a first sensor to acquire first measurement data, and (b) measuring body temperature of the sensing target person with use of a second sensor to acquire second measurement data.
  • the abnormality notification method further includes (c) determining whether or not the sensing target person is in a single or any one of a plurality of predetermined states in accordance with the first measurement data acquired by the first sensor, and (d) comparing reference body temperature for the single or any one of the plurality of predetermined states preliminarily stored in a memory unit with the body temperature of the sensing target person indicated by the second measurement data acquired by the second sensor when the sensing target person is determined as being in the predetermined state.
  • the abnormality notification method includes accordingly determining whether or not the sensing target person has body temperature abnormality, (e) generating alerting information for abnormality notification, when the sensing target person is determined as having body temperature abnormality, and (f) outputting the generated alerting information.
  • the present disclosure achieves accurate detection of body temperature abnormality of a sensing target person.
  • FIG. 1 is an explanatory diagram depicting a schematic configuration of an abnormality notification system according to a first exemplary embodiment of the present disclosure.
  • FIG. 2 is a block diagram depicting an entire configuration of the abnormality notification system according to the first exemplary embodiment of the present disclosure.
  • FIG. 3 is a flowchart depicting processing executed by the abnormality notification system according to the first exemplary embodiment of the present disclosure.
  • FIG. 4 is a block diagram depicting an entire configuration of an abnormality notification system according to a second exemplary embodiment of the present disclosure.
  • FIG. 5 is a chart indicating a data configuration of a normal body temperature table including registered normal body temperature and stored in a memory unit according to the present disclosure.
  • FIG. 6 is a chart indicating an exemplary data configuration of a history table including registered history data accumulated in the memory unit according to the present disclosure.
  • FIG. 7 is a flowchart depicting processing executed by the abnormality notification system according to the second exemplary embodiment of the present disclosure.
  • FIG. 8 is a flowchart depicting processing executed by an abnormality notification system according to a third exemplary embodiment of the present disclosure.
  • FIG. 9 is a flowchart depicting processing executed by an abnormality notification system according to a fourth exemplary embodiment of the present disclosure.
  • FIG. 10 is a diagram depicting an entire configuration of an abnormality notification system according to a fifth exemplary embodiment of the present disclosure.
  • FIG. 11 is a chart indicating a data configuration of a nursing care service history table according to the present disclosure.
  • FIG. 12 is a flowchart depicting processing executed by the abnormality notification system according to the fifth exemplary embodiment of the present disclosure.
  • Body temperature of a person varies in one day in accordance with states of the person such that the body temperature raises during active daytime and decreases during sleeping nighttime. It is accordingly important to consider body temperature variation according to states for accurate detection of body temperature abnormality of a person.
  • the present disclosure provides a technique of accurately detecting body temperature abnormality of a sensing target person.
  • a communication device configured to notify of abnormality of a sensing target person, and includes a first sensor configured to measure a state of the sensing target person to acquire first measurement data, a second sensor configured to measure a body temperature of the sensing target person to acquire second measurement data, and a memory unit configured to store a reference body temperature for a single or each of a plurality of predetermined states of the sensing target person.
  • the communication device further includes a state determiner configured to determine whether or not the sensing target person is in the single or any one of the plurality of predetermined states in accordance with the first measurement data acquired by the first sensor, and an abnormality determiner configured to compare the reference body temperature for the single or any one of the plurality of predetermined states with the body temperature of the sensing target person indicated by the second measurement data acquired by the second sensor when the state determiner determines that the sensing target person is in the single or any one of the plurality of predetermined states, to determine whether or not the sensing target person has body temperature abnormality.
  • the abnormality determiner generates alerting information for abnormality notification when determining that the sensing target person has body temperature abnormality.
  • the present aspect includes determining whether or not the sensing target person is in the single or any one of the plurality of predetermined states in accordance with the first measurement data measured by the first sensor.
  • the sensing target person is determined as being in the single or any one of the plurality of predetermined states
  • the reference body temperature for the single or any one of the plurality of predetermined states is compared with the body temperature indicated by the second measurement data measured by the second sensor to determine whether or not the sensing target person has body temperature abnormality.
  • the present aspect thus achieves accurate detection of body temperature abnormality of the sensing target person in consideration of body temperature varying in accordance with states.
  • the first sensor and the second sensor in the aspect acquire the first measurement data and the second measurement data in a constant period, respectively.
  • the communication device further includes a history data management unit configured to generate history data including the body temperature of the sensing target person acquired from the second measurement data and associated with the single or any one of the plurality of predetermined states, and accumulating the history data in the memory unit when the first measurement data acquired by the first sensor indicates that the sensing target person is in the single or any one of the plurality of predetermined states.
  • the communication device further includes a reference body temperature management unit configured to analyze the history data, calculate the reference body temperature for single or any one of the plurality of predetermined states, and store the reference body temperature in the memory unit.
  • the present aspect includes further analyzing the history data associating the first measurement data and the second measurement data on the sensing target person to calculate the reference body temperature for the single or each of the plurality of predetermined states, and storing the reference body temperature in the memory unit.
  • the present aspect thus achieves accurate detection of body temperature abnormality of the sensing target person in accordance with the reference body temperature appropriate for the sensing target person.
  • the first sensor may be constituted by a radio wave sensor and the second sensor may be constituted by a thermal image sensor.
  • the first sensor is constituted by the radio wave sensor and is configured to contactlessly detect the state of the sensing target person.
  • the second sensor is constituted by the thermal image sensor and is configured to contactlessly detect the body temperature of the sensing target person.
  • the first sensor in the above aspect may measure active mass of the sensing target person.
  • the active mass of the sensing target person is measured to achieve accurate detection of whether or not the sensing target person is in the predetermined state.
  • the state determiner in the above aspect may determine whether or not the sensing target person is in the single or any one of the plurality of predetermined states in accordance with the first measurement data and time of acquisition of the first measurement data.
  • the present aspect includes determining whether or not the sensing target person is in the single or any one of the plurality of predetermined states in further consideration of the time of acquisition of the first measurement data, to achieve more accurate detection of whether or not the sensing target person is in the single or any one of the plurality of predetermined states.
  • the reference body temperature management unit in the above aspect analyzes the history data, calculates normal body temperature of the sensing target person for each of the predetermined states as the reference body temperature, and stores the normal body temperature in the memory unit.
  • the abnormality determiner may determine that the body temperature of the sensing target person has abnormality when the body temperature of the sensing target person measured by the second sensor is higher than the normal body temperature for the single or any one of the plurality of predetermined states by at least a certain degree.
  • the present aspect includes analyzing the history data on the sensing target person to calculate the normal body temperature of the sensing target person in the single or any one of the plurality of predetermined states and detect whether or not the sensing target person has body temperature abnormality with reference to the normal body temperature. This enables more accurate detection of body temperature abnormality of the sensing target person.
  • the state determiner in the above aspect detects whether or not the sensing target person is present in accordance with the first measurement data acquired by the first sensor.
  • the abnormality determiner may start the second sensor only in a case where the state determiner detects presence of the sensing target person.
  • the second sensor is started only in the case where the sensing target person is present. This saves electricity consumption of the second sensor.
  • the state determiner in the above aspect detects whether or not the sensing target person is present in accordance with the first measurement data acquired by the first sensor.
  • the abnormality determiner does not need to determine whether or not the body temperature of the sensing target person has abnormality until a first period elapses after detection.
  • the sensing target person corresponds to a nursed person subjected to a nursing care service in the above aspect.
  • the communication device is connected, via a network, to a nursing care server configured to record a history of the nursing care service received by the nursed person.
  • the abnormality determiner determines whether or not a second period has elapsed after the nursed person receives the nursing care service with reference to the history of the nursing care service, and does not need to determine whether or not the body temperature of the nursed person has abnormality until the second period elapses.
  • the second sensor in the above aspect is constituted by a thermal image sensor configured to measure, as the first measurement data, thermal image data indicating temperature distribution in a measurement range around the second sensor.
  • the memory unit preliminarily stores positional information indicating a position of the sensing target person staying in the measurement range.
  • the abnormality determiner may compare coordinates of the persons in the thermal image data with the positional information to determine which one of the plurality of persons is the sensing target person.
  • the present aspect achieves accurate detection of body temperature abnormality of the sensing target person even in a case where a plurality of persons is present in the measurement range of the second sensor.
  • FIG. 1 is an explanatory diagram depicting a schematic configuration of abnormality notification system 1 according to the first exemplary embodiment of the present disclosure.
  • Abnormality notification system 1 includes first sensor 110 , second sensor 120 , and terminal device 200 .
  • First sensor 110 contactlessly detects a state of target person P 1 as a sensing target.
  • Second sensor 120 contactlessly detects body temperature of target person P 1 .
  • First sensor 110 and second sensor 120 may be installed in room R 10 of target person P 1 .
  • First sensor 110 and second sensor 120 may be incorporated in electrical equipment (e.g. an air conditioner) installed in room R 10 .
  • electrical equipment e.g. an air conditioner
  • Room R 10 is a habitable room of target person P 1 in a facility like a retirement home or a hospital. Room R 10 is equipped with bed 103 for target person P 1 . Room R 10 may be a room alternatively located in a house of target person P 1 .
  • Abnormality notification system 1 determines whether or not target person P 1 is in a specific state (a state immediately after rising is exemplarily adopted) in accordance with active mass detected by first sensor 110 .
  • Abnormality notification system 1 detects body temperature of target person P 1 from data acquired by second sensor 120 when target person P 1 is in the state immediately after rising.
  • Abnormality notification system 1 compares the detected body temperature of target person P 1 with preliminarily set normal body temperature of target person P 1 in the state immediately after rising.
  • Abnormality notification system 1 determines whether or not target person P 1 has body temperature abnormality (whether or not the body temperature and the normal body temperature of target person P 1 are largely different from each other). If target person P 1 has body temperature abnormality, abnormality notification system 1 generates alerting information and transmits the alerting information to terminal device 200 .
  • Terminal device 200 may be disposed in a room of carer P 2 (exemplifying a manager) who nurses target person P 1 in the facility. Terminal device 200 having received the alerting information, outputs at least one of alerting sound and an alerting image to notify carer P 2 of body temperature abnormality of target person P 1 . Carer P 2 is thus promptly notified of body temperature abnormality of target person P 1 .
  • FIG. 2 is a block diagram depicting an entire configuration of abnormality notification system 1 according to the first exemplary embodiment.
  • Abnormality notification system 1 includes communication device 100 and terminal device 200 .
  • Communication device 100 includes first sensor 110 , second sensor 120 , and processing unit 130 .
  • Communication device 100 is exemplarily incorporated in the electrical equipment installed in room R 10 as described above.
  • Communication device 100 may alternatively be constituted by a dedicated device provided separately from the electrical equipment.
  • Communication device 100 may still alternatively be constituted such that processing unit 130 is incorporated in the electrical equipment, and first sensor 110 and second sensor 120 are provided outside the electrical equipment.
  • first sensor 110 and second sensor 120 may be disposed, for example, on a ceiling of room R 10 , at bed 103 , or adjacent to bed 103 .
  • Communication device 100 includes constituent elements part or entirety of which may be constituted by a cloud server.
  • Terminal device 200 is constituted by a computer installed in the room of carer P 2 , and is communicably connected to communication device 100 via a network including at least one of a wireless local area network (LAN), a wired LAN, and a mobile phone communication network.
  • Terminal device 200 may be constituted by a stationary computer or a mobile terminal such as a smartphone or a tablet terminal carried by carer P 2 .
  • Terminal device 200 includes constituent elements part or entirety of which may be incorporated in a separate reporting device such as a nurse call system.
  • First sensor 110 measures a state or the like of target person P 1 to acquire active mass data (exemplifying first measurement data).
  • First sensor 110 includes first sensing unit 111 and first transmitter 112 .
  • First sensing unit 111 applies, to target person P 1 , a radio wave containing a microwave in a 24 GHz band or the like, and receives a reflected wave from target person P 1 .
  • First sensing unit 111 includes a radio wave sensor configured to detect frequency change (the Doppler effect) of the applied radio wave and the reflected wave caused in accordance with moving speed of target person P 1 , and acquire active mass data indicating active mass of target person P 1 from the frequency change thus detected.
  • First sensing unit 111 may adopt a system of detecting a target object other than the Doppler system.
  • First sensing unit 111 may adopt a frequency modulated continuous wave (FMCW) system or the like.
  • FMCW frequency modulated continuous wave
  • First transmitter 112 transmits the active mass data acquired by first sensing unit 111 to processing unit 130 in a predetermined sampling period.
  • Second sensor 120 measures body temperature of target person P 1 .
  • Second sensor 120 includes second sensing unit 121 and second transmitter 122 .
  • Second sensing unit 121 may be constituted by a thermal image sensor configured to measure, in a predetermined sampling period, thermal image data (exemplifying second measurement data) indicating temperature distribution in the measurement range.
  • the sampling period of second sensing unit 121 may be equal to or different from the sampling period of first sensing unit 111 . For easier description, the following will assume that these sampling periods are equal to each other.
  • Second transmitter 122 transmits the thermal image data measured by second sensing unit 121 to processing unit 130 in a constant period.
  • First sensor 110 is installed in room R 10 and is configured to apply a radio wave toward bed 103 .
  • Second sensor 120 is installed in room R 10 such that the measurement range includes bed 103 .
  • Specific target person P 1 as a measurement target is preliminarily provided with an identifier.
  • First sensor 110 and second sensor 120 associate the active mass data and the thermal image data with the identifier and transmit the acquired data to processing unit 130 . Even in a case where there is a plurality of target persons P 1 as monitoring targets, processing unit 130 can identify specific target person P 1 out of the plurality of target persons P 1 .
  • first transmitter 112 and second transmitter 122 are each constituted by an input/output interface configured to communicate with a processor such as a central processing unit (CPU) constituting processing unit 130 .
  • first transmitter 112 and second transmitter 122 are each constituted by a communication circuit including at least one of a wireless LAN and a wired LAN.
  • Processing unit 130 is constituted by a computer including a processor such as a CPU and a memory, and includes first receiver 131 , state determiner 132 , abnormality determiner 133 , memory unit 134 , third transmitter 135 , history data management unit 136 , and reference body temperature management unit 137 .
  • First receiver 131 receives the active mass data transmitted from first transmitter 112 , and receives the thermal image data transmitted from second transmitter 122 .
  • first receiver 131 is constituted by an input/output interface configured to communicate with first sensor 110 and second sensor 120 .
  • first receiver 131 is constituted by a communication circuit including at least one of a wired LAN and a wireless LAN.
  • State determiner 132 determines whether or not target person P 1 is in the specific state (exemplifying a predetermined state) in accordance with the active mass data measured by first sensor 110 .
  • exemplary adopted as the specific state is the state immediately after rising in this case. Examples of the specific state also include a sleeping state, an eating state, and a state immediately before resting.
  • State determiner 132 calculates feature quantity or the like from the active mass data, and determines that target person P 1 is in the specific state if the calculated feature quantity is similar to preliminarily set feature quantity for the specific state.
  • Adoptable examples of the feature quantity include a temporal variation pattern of a value acquired by substituting the active mass data for a predetermined function (e.g. a Cole formula).
  • abnormality determiner 133 compares the normal body temperature (exemplifying reference body temperature) for the specific state with the body temperature of target person P 1 indicated by the thermal image data measured by second sensor 120 .
  • Abnormality determiner 133 thus determines whether or not target person P 1 has body temperature abnormality.
  • Abnormality determiner 133 extracts a region indicating target person P 1 from the thermal image data through image processing, and calculates a representative temperature value (e.g. an average value or a median) in the extracted region.
  • Abnormality determiner 133 fixes body temperature for the calculated average temperature value in accordance with a body temperature conversion table or a body temperature conversion function preliminarily set and indicating relation between temperature and body temperature.
  • Abnormality determiner 133 then calculates the fixed body temperature as body temperature of target person P 1 .
  • Normal body temperature corresponds to body temperature of target person P 1 in a normal state.
  • the body temperature conversion table or the body temperature conversion function may not be preliminarily set but may alternatively be fixed in accordance with a temperature measurement result of target person P 1 while the system is in operation.
  • the body temperature conversion table or the body temperature conversion function may still alternatively be calibrated so as to be optimal for the target person in accordance with a preliminarily set function.
  • body temperature information measured with use of an axillary thermometer or the like may be combined with the thermal image data to generate a transfer function.
  • Abnormality determiner 133 reads normal body temperature immediately after rising as reference body temperature from memory unit 134 , and determines that target person P 1 has body temperature abnormality if the fixed body temperature of target person P 1 is higher than the normal body temperature thus read by at least a certain degree.
  • Adoptable examples of the certain degree include preliminarily set values such as 0.5 degrees, one degree, 1.5 degrees, and 2.0 degrees.
  • Abnormality determiner 133 generates alerting information to notify carer P 2 for target person P 1 of abnormality when determining that target person P 1 has body temperature abnormality.
  • the alerting information exemplarily includes the identifier for distinction of target person P 1 from other target persons, and the body temperature.
  • the thermal image data may alternatively not be converted to body temperature of target person P 1 .
  • temperature of target object P 1 may be acquired continuously and alerting information may be generated when the temperature exceeds a certain threshold.
  • body temperature abnormality may alternatively be determined through comparison between temperature in the normal state and relative temperature, such as whether or not the body temperature is higher than the temperature in the normal state by at least a certain degree.
  • Memory unit 134 may be constituted by a nonvolatile memory device, for example, and preliminarily stores the normal body temperature of target person P 1 in the specific state.
  • Third transmitter 135 may be constituted by a communication circuit configured to communicate with terminal device 200 . Third transmitter 135 transmits alerting information to terminal device 200 when abnormality determiner 133 determines that target person P 1 has body temperature abnormality.
  • history data management unit 136 When the active mass data measured by first sensor 110 indicates that target person P 1 is in the specific state, history data management unit 136 generates, as history data, the body temperature of target person P 1 acquired from the thermal image data measured by second sensor 120 , and accumulates the history data in memory unit 134 .
  • state determiner 132 determines that the active mass data indicates target person P 1 in the specific state
  • history data management unit 136 accumulates the body temperature of target person P 1 fixed in accordance with the thermal image data by abnormality determiner 133 , as history data in memory unit 134 .
  • Memory unit 134 thus accumulates body temperature of target person P 1 in the specific state.
  • Reference body temperature management unit 137 analyzes the history data accumulated in memory unit 134 to calculate normal body temperature for the specific state and store the normal body temperature in memory unit 134 . In a case where memory unit 134 accumulates history data for a certain period (e.g. one or two months), reference body temperature management unit 137 calculates an average value of body temperature values of target person P 1 included in the accumulated history data and stores the calculated average value as normal body temperature of target person P 1 in memory unit 134 .
  • a certain period e.g. one or two months
  • reference body temperature management unit 137 may calculate, as normal body temperature of target person P 1 , an average value of all body temperature values accumulated in memory unit 134 , or may calculate, as normal body temperature of target person P 1 , an average value of body temperature values during a latest certain period.
  • Reference body temperature management unit 137 may calculate normal body temperature each time a certain period elapses. Alternatively, reference body temperature management unit 137 may initially calculate normal body temperature after a certain period elapses, and may later calculate normal body temperature each time body temperature values are accumulated in memory unit 134 . Still alternatively, reference body temperature management unit 137 may calculate normal body temperature of target person P 1 not in accordance with elapse of such a certain period but in accordance with accumulation of a certain number of history data in memory unit 134 .
  • Terminal device 200 includes second receiver 201 , processing unit 202 , display unit 203 , and speaker 204 .
  • Second receiver 201 may be constituted by a communication circuit configured to communicate with communication device 100 , receives the alerting information transmitted from third transmitter 135 , and transmits the alerting information to processing unit 202 .
  • Processing unit 202 having acquired the alerting information from second receiver 201 causes display unit 203 to display the alerting information as the alerting image in order to notify carer P 2 of body temperature abnormality of target person P 1 .
  • Processing unit 202 having acquired the alerting information from second receiver 201 causes speaker 204 to output the alerting sound in order to notify carer P 2 of body temperature abnormality of target person P 1 .
  • the alerting image includes a name and a face image of target person P 1 , as well as a message indicating body temperature abnormality.
  • Adoptable examples of the alerting sound include alarm sound or a speech message on body temperature abnormality of target person P 1 .
  • Display unit 203 may be constituted by an organic electroluminescence (EL) panel or a liquid crystal panel, and is configured to display an alerting image.
  • Speaker 204 is configured to output alerting sound.
  • Display unit 203 may display body temperature information for each target person, including biological information acquired by first sensor 110 and other sensing information acquired by at least one of a temperature and humidity sensor and an illuminance sensor.
  • Display unit 203 may constitute part of a nurse call system or a nursing care business system, and may be configured to display body temperature information along with other information on target person P 1 .
  • FIG. 3 is a flowchart depicting processing executed by abnormality notification system 1 according to the first exemplary embodiment. Assume that the processing in this flowchart is executed in a predetermined sampling period in the present exemplary embodiment.
  • State determiner 132 initially acquires latest active mass data measured by first sensor 110 (S 301 ).
  • State determiner 132 subsequently analyzes the active mass data measured by first sensor 110 (S 302 ). State determiner 132 then determines whether or not target person P 1 is in the specific state (the state immediately after rising in this case) in accordance with an analysis result (S 303 ). In a case where target person P 1 is in the specific state (YES in S 303 ), abnormality determiner 133 acquires latest thermal image data measured by second sensor 120 (S 304 ). In another case where target person P 1 is not in the specific state (NO in S 303 ), the processing flow returns to step S 301 .
  • Abnormality determiner 133 subsequently calculates body temperature of target person P 1 from the acquired thermal image data (S 305 ).
  • Abnormality determiner 133 determines whether or not the calculated body temperature is more than or equal to a value acquired by adding a certain degree to the normal body temperature in the specific state stored in memory unit 134 (S 306 ). In a case where the calculated body temperature is more than or equal to the value acquired by adding the certain degree to the normal body temperature in the specific state stored in memory unit 134 (YES in S 306 ), abnormality determiner 133 determines that target person P 1 has body temperature abnormality (S 307 ).
  • Abnormality determiner 133 subsequently generates alerting information to notify carer P 2 of body temperature abnormality of target person P 1 and causes third transmitter 135 to transmit the alerting information (S 308 ).
  • step S 305 In another case where the body temperature calculated in step S 305 is less than the value acquired by adding the certain degree to the normal body temperature in the specific state stored in memory unit 134 (NO in S 306 ), the processing flow proceeds to step S 309 .
  • History data management unit 136 subsequently accumulates the body temperature calculated in step S 305 as history data in memory unit 134 (S 309 ).
  • reference body temperature management unit 137 calculates normal body temperature of target person P 1 from the accumulated history data (S 311 ).
  • Reference body temperature management unit 137 subsequently updates the normal body temperature currently stored in memory unit 134 to the calculated normal body temperature (S 312 ).
  • processing in step S 312 ends, the processing flow returns to step S 301 .
  • reference body temperature management unit 137 causes the processing flow to return to step S 301 .
  • abnormality notification system 1 compares reference body temperature for the specific state with body temperature indicated by thermal image data measured by second sensor 120 when target person P 1 is determined as being in the specific state in accordance with active mass data measured by first sensor 110 . It is thus determined whether or not target person P 1 has body temperature abnormality. Abnormality notification system 1 accordingly achieves accurate detection of body temperature abnormality of a sensing target person in consideration of body temperature varying in accordance with states.
  • FIG. 4 is a block diagram depicting an entire configuration of abnormality notification system 1 A according to the second exemplary embodiment.
  • Abnormality notification system 1 A includes memory unit 134 A configured to store normal body temperature values for a plurality of specific states.
  • memory unit 134 A configured to store normal body temperature values for a plurality of specific states.
  • FIG. 4 depicts constituent elements that are named identically with those according to the first exemplary embodiment but function differently. Such constituent elements each have symbol A at the end of the reference marks denoted in the first exemplary embodiment.
  • State determiner 132 A determines in which one of preliminarily set specific states (exemplifying a plurality of predetermined states) target person P 1 is in accordance with the active mass data measured by first sensor 110 .
  • Adoptable examples of the plurality of specific states include the state immediately after rising, the sleeping state, the eating state, and the state immediately before resting.
  • the adoptable examples may further include a reading state, a state of watching TV, and a state of executing handwork.
  • State determiner 132 A determines that target person P 1 is in the sleeping state in an exemplary case where the active mass data has feature quantity similar to preliminarily set feature quantity for the sleeping state. State determiner 132 A determines that target person P 1 is in the eating state if the active mass data has feature quantity similar to preliminarily set feature quantity for the eating state, and determines that target person P 1 is in the state immediately before resting if the active mass data has feature quantity similar to preliminarily set feature quantity for the state immediately before resting.
  • abnormality determiner 133 A reads normal body temperature for the single specific state from memory unit 134 A.
  • Abnormality determiner 133 A compares the read normal body temperature with the body temperature of target person P 1 indicated by the thermal image data measured by second sensor 120 to determine whether or not target person P 1 has body temperature abnormality.
  • Memory unit 134 A stores normal body temperature for each of the plurality of specific states.
  • FIG. 5 is a chart indicating a data configuration of normal body temperature table T 1 including registered normal body temperature stored in memory unit 134 A.
  • Normal body temperature table T 1 includes normal body temperature (T_11, T_12, T_14, T_15) for the specific states, namely, “immediately after rising”, “sleeping”, “eating”, and “immediately before resting”, respectively.
  • state determiner 132 A determines that target person P 1 is currently in the state of “immediately after rising”.
  • abnormality determiner 133 A acquires normal body temperature T_11 for the state of “immediately after rising” from memory unit 134 A, and compares normal body temperature T_11 with current body temperature of target person P 1 . It is thus determined whether or not target person P 1 has body temperature abnormality.
  • history data management unit 136 A When the active mass data measured by first sensor 110 indicates that target person P 1 is in any one of the plurality of specific states, history data management unit 136 A generates history data including the single specific state associated with the body temperature of target person P 1 acquired from the thermal image data measured by second sensor 120 , and accumulates the history data in memory unit 134 A.
  • FIG. 6 is a chart indicating an exemplary data configuration of history table T 2 including registered history data accumulated in memory unit 134 A.
  • History table T 2 is constituted by a database including each record associated with single registered history data, and has fields of “time”, “specific state”, and “body temperature”.
  • the field “time” stores time of registration of history data in memory unit 134 A.
  • the time in this case has a data structure of year/month/time.
  • the field “specific state” stores the specific state of target person P 1 upon registration of history data.
  • the field “body temperature” stores body temperature of the target person upon registration of history data.
  • FIG. 6 exemplifies a case where the active mass data indicates that target person P 1 is in the state immediately after rising and the thermal image data indicates that target person P 1 has body temperature at T01 degrees at 04:30 on Jan. 1, 2017.
  • the fields “time”, “specific state”, and “body temperature” store “2017 Jan. 1/04:30”, “immediately after rising”, and “T01”, respectively.
  • Reference body temperature management unit 137 A refers to history table T 2 accumulated in memory unit 134 A, sorts body temperature values in the history data by the specific states, and calculates an average value of the body temperature for each of the specific states.
  • Reference body temperature management unit 137 A calculates normal body temperature for each of the plurality of specific states, and stores the calculated normal body temperature in memory unit 134 A. This establishes normal body temperature table T 1 indicated in FIG. 5 .
  • History table T 2 indicated in FIG. 6 exemplifies a case where reference body temperature management unit 137 A sorts the history data by the specific states including “immediately after rising”, “eating”, and “immediately before resting”, and calculates an average value of body temperature from the sorted history data. This achieves calculation of normal body temperature for each of the specific states.
  • Reference body temperature management unit 137 A has timing for calculation of normal body temperature, and variation of a range of the history data referred to for calculation of normal body temperature. Such timing and variation are the same as those according to the first exemplary embodiment.
  • FIG. 7 is a flowchart depicting processing executed by abnormality notification system 1 A according to the second exemplary embodiment.
  • FIG. 7 includes processing steps same as those depicted in FIG. 3 and denoted by same processing numbers. Such processing steps will-not be described repeatedly.
  • step S 701 subsequent to step S 302 , state determiner 132 A determines whether or not target person P 1 is in any one of the plurality of specific states. If target person P 1 is not in any one of the specific states (NO in S 701 ), the processing flow returns to S 301 . If target person P 1 is in any one of the specific states (YES in S 701 ), the processing flow proceeds to S 304 .
  • step S 702 subsequent to step S 305 abnormality determiner 133 A reads, from memory unit 134 A, normal body temperature for the single specific state determined in step S 701 .
  • step S 703 subsequent to step S 308 history data management unit 136 A associates the single specific state determined in step S 701 with the body temperature of target person P 1 calculated in step S 305 and current time to generate history data, and accumulates the history data in memory unit 134 A.
  • History table T 2 indicated in FIG. 6 thus includes history data registered sequentially.
  • reference body temperature management unit 137 A sorts the history data stored in history table T 2 indicated in FIG. 6 by the specific states, and calculates an average value of body temperature for each history data thus sorted. This achieves calculation of normal body temperature for each of the specific states.
  • Reference body temperature management unit 137 A subsequently updates the normal body temperature for each of the specific states currently stored in memory unit 134 A to the normal body temperature calculated for each of the specific states (S 312 ).
  • Abnormality notification system 1 A determines whether or not target person P 1 has body temperature abnormality if target person P 1 is in any one of plurality of the specific states. This configuration more precisely monitors whether or not target person P 1 has body temperature abnormality.
  • Normal body temperature table T 1 stores normal body temperature for each of the plurality of specific states, to enable accurate detection of whether or not target person P 1 has body temperature abnormality.
  • the third exemplary embodiment provides abnormality notification system 1 B configured to turn ON second sensor 120 only in a case where first sensor 110 detects target person P 1 .
  • the present exemplary embodiment adopts the entire configuration depicted in FIG. 2 according to the first exemplary embodiment.
  • the present exemplary embodiment may alternatively adopt the entire configuration depicted in FIG. 4 according to the second exemplary embodiment.
  • FIG. 8 is a flowchart depicting processing executed by abnormality notification system 1 B according to the third exemplary embodiment.
  • step S 801 state determiner 132 determines whether or not first sensor 110 has detected target person P 1 in accordance with the active mass data acquired by first sensor 110 .
  • state determiner 132 determines that target person P 1 is present.
  • State determiner 132 subsequently causes first receiver 131 to transmit, to second sensor 120 , a control command to turn ON second sensor 120 in order to turn ON second sensor 120 (S 802 ). If no target person is detected (NO in S 801 ), the processing flow proceeds to step S 803 . In step S 803 , state determiner 132 causes first receiver 131 to transmit, to second sensor 120 , a control command to turn OFF second sensor 120 in order to turn OFF second sensor 120 . When processing in step S 803 ends, the processing flow returns to step S 801 .
  • step S 804 abnormality notification system 1 B executes a measurement flow and causes the processing flow to return to step S 801 .
  • the measurement flow may follow the flowchart depicted in FIG. 3 and described in the first exemplary embodiment, or the flowchart depicted in FIG. 7 and described in the second exemplary embodiment.
  • second sensor 120 is started only in the case where target person P 1 is present. This saves electricity consumption of second sensor 120 .
  • First sensor 110 is assumed to be constantly driven in the present exemplary embodiment.
  • the fourth exemplary embodiment provides abnormality notification system 1 C configured not to determine whether or not target person P 1 has body temperature abnormality until a first period elapses if absence of target person P 1 is detected and presence of target person P 1 is then detected.
  • Examples of the case of transition from absence to presence of target person P 1 in the present exemplary embodiment include a case where target person P 1 having been out returns to room R 10 .
  • the present exemplary embodiment adopts the entire configuration depicted in FIG. 2 according to the first exemplary embodiment.
  • the present exemplary embodiment may alternatively adopt the entire configuration depicted in FIG. 4 according to the second exemplary embodiment.
  • FIG. 9 is a flowchart depicting processing executed by abnormality notification system 1 C according to the fourth exemplary embodiment.
  • State determiner 132 initially determines whether or not target person P 1 has returned to room R 10 (S 901 ). If the active mass data transmitted from first sensor 110 is detected to have change from a value less than the predetermined reference value to a value more than or equal to the reference value indicating presence of target person P 1 , state determiner 132 determines that target person P 1 has returned to room R 10 .
  • abnormality determiner 133 determines whether or not the first period has elapsed (S 902 ).
  • Adoptable examples of the first period include a period expected to be needed for active mass of target person P 1 to return to normal active mass. If the first period has not elapsed (NO in S 902 ), the processing flow returns to step S 902 .
  • step S 903 abnormality notification system 1 C executes a measurement flow and causes the processing flow to return to step S 901 .
  • the measurement flow may follow the flowchart depicted in FIG. 3 and described in the first exemplary embodiment, or the flowchart depicted in FIG. 7 and described in the second exemplary embodiment.
  • Abnormality notification system 1 C does not determine whether or not target person P 1 has body temperature abnormality in a state where active mass is higher than normal active mass immediately after target person P 1 returns into the room, to prevent erroneous detection of body temperature abnormality of target person P 1 .
  • the fifth exemplary embodiment provides abnormality notification system 1 D configured not to determine whether or not target person P 1 has body temperature abnormality during a second period immediately after target person P 1 receives a specific nursing care service.
  • Communication device 100 and terminal device 200 according to the present exemplary embodiment adopt the configurations depicted in FIG. 2 according to the first exemplary embodiment.
  • Communication device 100 and terminal device 200 may alternatively adopt the configurations depicted in FIG. 4 according to the second exemplary embodiment.
  • FIG. 10 is a block diagram depicting an entire configuration of abnormality notification system 1 D according to the fifth exemplary embodiment.
  • Abnormality notification system 1 D includes communication device 100 and terminal device 200 connected to nursing care server 300 via network NT.
  • Adoptable examples of network NT include a public communication network such as the Internet.
  • Nursing care server 300 is constituted by a computer including a processor, a communication circuit, and the like, and is configured to record a history of a nursing care service received by target person P 1 .
  • Nursing care server 300 is managed by a nursing care service provider who provides target person P 1 with the nursing care service.
  • Adoptable examples of the nursing care service provider include a facility provider described with reference to FIG. 1 . If room R 10 is located in the house of target person P 1 , the nursing care service provider may be a provider of at-home nursing care services.
  • Nursing care server 300 includes memory 301 .
  • Memory 301 may be constituted by a nonvolatile memory device, and stores nursing care service history table T 3 indicated in FIG. 11 .
  • FIG. 11 is a chart indicating a data configuration of nursing care service history table T 3 .
  • Nursing care service history table T 3 is constituted by a database including each record associated with registered history data on a single nursing care service, and has fields of “period” and “details of nursing care service”.
  • the field “period” stores a period of the nursing care service received by target person P 1 .
  • the field “details of nursing care service” stores details of a nursing care service received by target person P 1 .
  • Adoptable examples of the details of a nursing care service include a bathing service of assisting target person P 1 with bathing by carer P 2 , and an exercising service of assisting target person P 1 with exercising by carer P 2 .
  • the details of nursing care services are merely exemplarily indicated in FIG. 11 , and other nursing care services may be registered where appropriate.
  • target person P 1 received a bathing service from 17:00 to 18:00 on Jan. 1, 2017, so that FIG. 11 has a first record including “2017 Jan. 1/17:00-18:00” and “bathing service”.
  • FIG. 12 is a flowchart depicting processing executed by abnormality notification system 1 D according to the fifth exemplary embodiment.
  • step S 1201 state determiner 132 determines whether or not first sensor 110 has detected target person P 1 in accordance with the active mass data acquired by first sensor 110 . Details of this processing are similar to those of the processing in step S 801 depicted in FIG. 8 .
  • Abnormality determiner 133 subsequently refers to nursing care service history table T 3 indicated in FIG. 11 and determines whether or not the second period has elapsed after target person P 1 received the specific nursing care service (S 1202 ).
  • the specific nursing care service in this case increases active mass of target person P 1 and needs a certain period to return the active mass of target person P 1 to normal active mass after the nursing care service ends.
  • Examples of the specific nursing care service include the bathing service and the exercising service.
  • Adoptable examples of the second period include a period expected to be needed for active mass of target person P 1 to return to normal active mass after the nursing care service ends.
  • step S 1202 If the second period has not elapsed after receipt of the specific nursing care service (NO in S 1202 ), the processing flow returns to step S 1202 . If the second period has elapsed after receipt of the specific nursing care service (YES in S 1202 ), the processing flow proceeds to step S 1203 .
  • step S 1203 abnormality notification system 1 D executes a measurement flow and causes the processing flow to return to step S 1201 .
  • the measurement flow may follow the flowchart depicted in FIG. 3 and described in the first exemplary embodiment, or the flowchart depicted in FIG. 7 and described in the second exemplary embodiment.
  • Abnormality notification system 1 D does not determine whether or not target person P 1 has body temperature abnormality in a state where active mass is higher than normal active mass immediately after target person P 1 receives the specific nursing care service, to prevent erroneous detection of body temperature abnormality of target person P 1 .
  • the sixth exemplary embodiment provides abnormality notification system 1 E configured to determine whether or not target person P 1 is in the specific state with reference to time of acquisition of the active mass data as well as the active mass data.
  • the present exemplary embodiment adopts the entire configuration depicted in FIG. 4 according to the second exemplary embodiment.
  • the present exemplary embodiment may alternatively adopt the entire configuration depicted in FIG. 2 according to the first exemplary embodiment.
  • State determiner 132 A determines whether or not target person P 1 is in any one of the plurality of specific states in accordance with the active mass data transmitted from first sensor 110 , as in the first exemplary embodiment. State determiner 132 A subsequently determines that the single specific state thus determined is true if the time of acquisition of the active mass data is included in a time zone preliminarily set for the single specific state thus determined. State determiner 132 A determines that the determined state is false if the time of acquisition of the active mass data is not included in the time zone preliminarily set for the single specific state thus determined.
  • state determiner 132 A is configured to execute the above processing.
  • state determiner 132 A includes a state determination table preliminarily setting a time zone enabling determination as being true for each of the specific states, and determines whether the specific state determined in accordance with the active mass data is true or false with reference to the state determination table.
  • Abnormality notification system 1 E determines whether or not target person P 1 is in the specific state in further consideration of time of acquisition of the active mass data. This enables more accurate detection of whether or not target person P 1 is in the specific state.
  • the seventh exemplary embodiment provides abnormality notification system IF configured to detect target person P 1 out of a plurality of persons detected in accordance with the thermal image data.
  • the present exemplary embodiment adopts the entire configuration depicted in FIG. 2 according to the first exemplary embodiment.
  • the present exemplary embodiment may alternatively adopt the entire configuration depicted in FIG. 4 according to the second exemplary embodiment.
  • Memory unit 134 preliminarily stores positional information indicating a position of target person P 1 staying in the measurement range around second sensor 120 .
  • FIG. 1 exemplarily adopts a region provided with bed 103 as a position where target person P 1 stays.
  • FIG. 1 assumes that bed 103 is positioned in the measurement range of second sensor 120 .
  • Adoptable examples of the positional information include coordinates data indicating the region provided with bed 103 in the thermal image data captured by second sensor 120 .
  • Abnormality determiner 133 determines that the thermal image data includes a plurality of persons in an exemplary case of detecting a plurality of regions each having a silhouette of a person in the thermal image data.
  • abnormality determiner 133 determines that the person corresponds to target person P 1 .
  • Abnormality determiner 133 may alternatively detect target person P 1 in consideration of movement of each person.
  • abnormality determiner 133 determines that a plurality of persons is present in accordance with the thermal image data
  • abnormality determiner 133 follows movement of each of the persons for a certain period and acquires length of a movement locus of each of the persons in accordance with the thermal image data.
  • the plurality of detected persons will include, in addition to target person P 1 , a person visiting target person P 1 , carer P 2 , and the like. The visiting person and carer P 2 are thus assumed to move more actively than target person P 1 .
  • abnormality determiner 133 determines that target person P 1 corresponds to the person having the shortest movement locus out of a plurality of persons each having a silhouette region overlapped with the region indicated by the positional information.
  • Abnormality determiner 133 may determine that target person P 1 corresponds to the person having the shortest movement locus if a plurality of persons is detected and there is no person having the silhouette region overlapped with the region indicated by the positional information. Abnormality determiner 133 may alternatively determine that target person P 1 corresponds to the person having the shortest movement locus in no consideration of the positional information.
  • the measurement range of second sensor 120 may include a plurality of target persons P 1 .
  • abnormality determiner 133 preliminarily stores, in memory unit 134 , positional information on the plurality of target persons P 1 associated with identifiers of the target persons P 1 .
  • Abnormality determiner 133 specifies target person P 1 in accordance with the identifier associated with the positional information on the region overlapped with the silhouette region and extracted from the thermal image data in a plurality of regions indicated by a plurality of positional information.
  • the present disclosure can adopt the following modification examples.
  • FIG. 2 exemplifies processing unit 130 including history data management unit 136 and reference body temperature management unit 137 , which may not be provided in the present disclosure.
  • memory unit 134 may store preliminarily set normal body temperature in place of normal body temperature calculated from history data.
  • FIG. 4 exemplifies processing unit 130 A including history data management unit 136 A and reference body temperature management unit 137 A, both of which may not be provided in the present disclosure.
  • memory unit 134 A may store preliminarily set normal body temperature for each state in place of normal body temperature for each state calculated from history data.
  • first sensor 110 constituted by a radio wave sensor.
  • first sensor 110 may be constituted by any other sensor configured to measure active mass of target person P 1 .
  • first sensor 110 may be constituted by a sensor configured to measure a heart rate or a brain wave.
  • state determiner 132 detects a state of target person P 1 in accordance with the heart rate or the brain wave.
  • first sensor 110 is described as a contactless sensor.
  • first sensor 110 may be constituted by a contact sensor.
  • second sensor 120 constituted by a thermal image sensor
  • second sensor 120 may be constituted by any other sensor configured to measure body temperature of target person P 1 .
  • second sensor 120 may be constituted by a contact thermometer.
  • the present disclosure significantly achieves accurate detection of body temperature abnormality of a sensing target person.
  • the present disclosure is thus usefully applicable to a communication device, an abnormality notification system, an abnormality notification method, and the like in a technical field of watching a nursed person and the like.
  • T 1 normal body temperature table
  • T 3 nursing care service history table
  • processing unit 202 processing unit

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CN110248593A (zh) 2019-09-17
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